code: def test_detect_variables_with_missing_data_in_variables_entered_by_user(
      df_na,
  ):
      imputer = AddMissingIndicator(
          missing_only=True, variables=["City", "Studies", "Age", "dob"]
      )
      X_transformed = imputer.fit_transform(df_na)
      assert imputer.variables == ["City", "Studies", "Age", "dob"]
      assert imputer.variables_ == ["City", "Studies", "Age"]
      assert X_transformed.shape == (8, 9)
      assert "City_na" in X_transformed.columns
      assert "dob_na" not in X_transformed.columns
      assert X_transformed["City_na"].sum() == 2
  
file_path: feature_engine/tests/test_imputation/test_missing_indicator.py
imports: import pytest
  from sklearn.pipeline import Pipeline
  from feature_engine.imputation import AddMissingIndicator
label_desc: Use image node_id 4 for calling a global function with example usage: test_detect_variables_with_missing_data_in_variables_entered_by_user(df_na) without return types